session 02_paper 26
TRANSCRIPT
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* Corresponding author. Abhishek verma
1M.Tech., Speech and Image Processing Lab, Indian Institute of Information Technology Allahabad 211012, Uttar Pradesh, India.
2Research Scholar, Speech and Image Processing Lab, Indian Institute of Information Technology Allahabad 211012, Uttar Pradesh, India.
3Professor,Department of Human-Computer Interaction, Indian Institute of Information Technology Allahabad 211012, Uttar Pradesh, India
Abstract
Keywords: Digital speech Tampering, Copy-Move Forgery, Audio Features, Neighbor Shift matching
1. Introduction
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Types of forgery in the audio contents
Insertion: Copy-Move:
Deletion: Substitution: Splicing:
Previous work
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A assive pproach to etect opyMve orgery in igital peech udioignal
2. Features Used
Root mean square value (RMS value): -
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Zero-crossing rate (ZCR): T
Spectral Flatness measure (SFM) :
Spectral Crest Factor (SCF):
Mel-Frequency Cepstral Coefficients (MFCC):
Power Spectral Density (Spectra Density Mean and Spectral Density Standard Deviation):
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A assive pproach to etect opy-ove orgery in igital peech udioignal
3. Proposed Method
.
DownSampling (Optional):-
Windowing of samples:-
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Feature Extraction/computation
.
Lexicographical Sorting:-
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A assive pproach to etect opy-ove orgery in igital peech udioignal
Detection of suspected copied region:-
Neighbor Shift matching: -
.
.
Detection and marking of Duplicated Region:-
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3.1 Algorithm-copy-move forgery detection of digital audio speech signal:-
.
Begin
End
4. Experimental result/Description
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A assive pproach to etect opy-ove orgery in igital peech udioignal
guess the question from
the answers guess the question from the answersguess
.
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5. Conclusion
Acknowledgement:
References
Dr. Girija Chetty (Ed.)
International Journal of Advanced Science and Technology
IEEE signal processing magazine
4th International
Congress on Image and Signal Processing
Advances in
Computers
IEEEWorkshop on Applications of Signal Processing to Audio and Acoustics 2001
ACM 978-1-60558-
058,MM&Sec08
International Journal of
Electronics and telecommunications
IEEE,
ICASSP
J. Audio Eng. Soc.,
IEEE Computer Society
.
Features used Percentage of false matching pair
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A assive pproach to etect opy-ove orgery in igital peech udioignal
ACM 978-1-59593-857-2
National Institute of Standards andTechnology, NISTIR 4930
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Index
A
Audio features, 186, 193
CCopy-move forgery, 184186, 188
detection algorithm, 191sample of, 185
D
Digital audiosdefine, 184
down sampling, 188
duplicated region, detection and marking of, 190experimental result/description, 191192feature extraction/computation, 189
flow chart, 188
lexicographical sorting, 189190MFCC, 187
neighbor shift matching, 190
PSD, 187root mean square value (RMS value), 186
SCF, 187188
SFM, 187188signal processing, 186188
suspected copied region, detection, 190windowing of samples, 188189
ZCR, 187
Digital forgery
define, 184types of, 185186
Digital speech tampering, 184
M
Mel-frequency cepstral coefficients (MFCC), 187
N
Neighbor shift matching, 185, 190
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P
Power spectral density (PSD), 187
R
Root mean square value (RMS value), 186
S
Spectral crest factor (SCF), 187188Spectral flatness measure (SFM), 187188
Z
Zero-crossing rate (ZCR), 187